Information privacy or data privacy refers to a relationship between collection of data and dissemination of data. With respect to various issues such as legal and personal, privacy protection of sensor data has become an important requirement. Privacy concerns usually exist wherever personally identifiable information is collected and stored. Such personally identifiable information if not handled carefully may reveal personal data during analysis. The challenge while protecting personal data or sensitive data lies in amount of privacy that should be given as per the private content present in any personally identifiable information.
Existing privacy methodologies introduces different privacy preserving techniques to counter the problem of privacy breaching attacks. However, arbitrary privacy preservation on sensitive data would be over provisioning, considers worst-case scenario and thus minimizes the utility and intelligence of the privacy preserved sensor data. So it is equally important to measure amount of privacy content in a data set to be privacy protected before applying any privacy preserving technique. This will help in identifying required privacy and will also reduce data distortion.
One such methodology to provide data privacy includes encryption of sensor data. Although encryption of sensor data may protect the private content present in the sensor data, however the encryption may destroy complete utility of the sensor data particularly in broadcast or storage, only the person with key can understand the full content of sensor data, but others in the broadcast mode will get illegible data. One of the important issues associated with respect to known privacy preserving techniques is that, more the strength of privacy preservation on sensor data more utility or intelligence is lost, makes sensor data useless. Without measuring the amount of privacy protection required, arbitrary privacy preservation results in irreversible utility loss to sensor data.